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NEWS & MUSINGS ON LA TECH STARTUPS

Category Archives: Go2Market – User Acq

I love the lean startup ethos and methodology. It is by far the best thing that has happened to the startup community since the onset of the internet-fuel renaissance in entrepreneurship. These days at MuckerLab, we try to utter the basic concepts (mvp, iteration, hypothesis testing, customer development, etc) as much as possible to help our entrepreneurs and ourselves stay on track. People that have heard me talk at panels and conferences probably think I’ve been brainwashed by the cult of Eric Ries, and I would be flattered. BUT certainly before the lean startup movement there were wildly successful and visionary entrepreneurs. And long after “lean” becomes indistinguishable from entrepreneurship itself, there will continue to be failures and disillusioned entrepreneurs. Lean is not a panacea or a blue print for success. It’s a framework and like any framework, it can be misused. After immersing ourselves in the ethos and watching our entrepreneurs apply the lean methodology in their startups, we are starting to learn more how to adjust and adapt the formula in different circumstances.

It is certainly a lot easier to apply the lean methodology to consumer focused businesses than it is enterprise focused businesses. In enterprise, lean works, but it takes more patience, rigor, and flexibility. Customer development will always improve the signal to noise ratio for better product-market fit; but given how hard it is to scale enterprise customer development, it is extremely important for entrepreneurs to be wary of any data they are gathering given the small sample size and potential for sample biases. If possible, I like to start the customer development process with a very wide funnel as to diversify across multiple segments within the target market . . . and quickly narrow down to a specific receptive segment as additional data comes in (essentially abandoning certain customers along the way).

In addition, the enterprise software business follows adoption patterns that are significantly closer to the “Geoffrey Moore” model than the “viral” adoption model we come to expect in the consumer Internet world. In enterprise, early product market fit is just that – early. Until the product has crossed chasm – it hasn’t. In this market, the traditional top down category marketing playbook is still the only playbook to cross the chasm. CIO’s often (for better and for worse) allocate their budgets based on latest trends and research that are heavily influenced by industry analysts (Gartner for example) – so enterprise software entrepreneurs will have to invest dollar and time to slowly build mindshare for its product category and company. Initial product market fit only buys an option to play in the big leagues where old games are still played by old dogs. Most enterprise companies will not come close to achieving the types of exponential growth more common in consumer product (in which signal will overwhelm any noise) until much later in their company lifecycle.

The other interesting dynamic we are seeing is that network effects driven businesses (e.g. marketplaces, social networks, UGC applications) also require a slightly more patient and acquisition focused approach to “lean.” By definition, these businesses need a critical mass of supply / demand (e.g. users and content ) to achieve their core value proposition. As a product or feature is released to market there is a huge temptation to declare the “test” a failure based on initial data when in fact it has nothing to do with the product but as a result of the lack of content and/or users. Pinterest famously stagnated with the same basic product for over a year before hitting a tipping point and taking off once the site achieved usage and user escape velocity. In short, it is more about market-market fit than it is product-market fit. The product’s objective is to retain users and reduce transactional or communications friction, but aggressive acquisition tactics and often lots of luck is needed to truly test for product market hypothesis. There is a tremendous focus on avoiding type I errors in the lean methodology, but avoiding type II errors are just as important to the eventual success of a startup.

There is one class I never missed in high school, Drivers Ed. I had been eyeing my sister’s red 1986 Honda Prelude for years – it was going to be my ticket to the teen age nirvana – ownership, freedom, status . . . and girls. Ro (Formsprings, RockYou) and Zhao (Betterworks, Farmville) were here the other day talking to our companies about the science of virality – looking around the room, it reminded me of my driver’s ed class. . . The topic was well known yet the words coming out of Ro and Zhao’s mouth seemed a bit foreign. Everyone in the room knew that every sentence was worth millions of dollars, yet despite all the concentration and furious note taking, the comprehension rate was only somewhere around 30%. There are things that can be taught, and there are things where someone can only point us in the right direction. Nothing replaces getting behind the wheel and trying to merge into highway traffic a few hundred times to get the hang of it.

People have been studying the subject since Hotmail took off in the dot com era. The Paypal mafia made it somewhat of a secret playbook for its members, while a new generation of masters sprung up around MySpace in the mid 2000s. It finally bled into the common consciousness during the recent Facebook era. Today, it is almost a prerequisite slide topic for any venture funding pitch.

Not going to regurgitate all the great stuff that’s already out there from people miles smarter than I am.

What is interesting is that given the amount of noise – hundreds of thousands of startup sites and apps, leveraging the same viral channels and techniques – the average virality (k-factor if you well) must surely be declining despite the best effort of many entrepreneurs. Further complicating the problem is that virality inherently benefits companies with existing scale. First, because a large “n” ( as in “n” number of infected), all else being equal, mathematically creates more opportunities for connections/infections. And second, because large amount traffic allows for testing a large # of permutations to create the most statistically efficient viral loop or conversion funnel. As a result, early stage companies that have achieve the highly sought after exponential growth are becoming black swan events – exceptions to the rule and arguably more based on luck than strategy. Unless an entrepreneur has “done it before” – almost everyone (especially VC’s) are highly discounting any acquisition and growth strategies based on “virality.” You just got to go out there and prove you have the viral chops to claim to know anything about the topic. (Plus VC’s don’t mind paying up for numbers so it’s good for everyone in the end.)

So what’s a startup to do to prove its chops? Certainly ignoring any viral channels/strategies is more than stupid. Here are a few things I’ve gathered along the way (including some I learned stole from talking to Ro & Zhao).

Understand Non-Linear Amplification – Traditional conversion funnel optimization creates linear improvements in the outcome – and often a few basis points improvement is simply not worth the effort required. (my eCPA dropped by 2 cents!). But in the viral loop context where the conversion funnel is repeated exponential number of times – every basis point improvement could potentially mean 2-3x increase in acquisition not too far down the line. (how much better will depend on other variable in the equation). As a result; don’t guess, have some basic understanding of how to create the best call to action for high CTR and test the hell out of every copy, color, placement, picture you include in your conversion funnel / viral loop.

Find On Ramps – Viral marketing doesn’t work by itself. You need to find a complementary acquisition channel to solve the cold start problem and to continue to “juice” the virality. By definition, viral growth requires a group of “patient zero’s” to work. Furthermore, more likely than not, it will take a few iteration of the conversion funnel/loop to get to the point where the K factor is above 1. As a result, everyone has to figure out a consistent channel for customer acquisition where virality can be bootstrapped. (this is one of the many reasons that when entrepreneurs ONLY talks about virality, they are typically screwed). Traditional customer acquisition techniques all work as on ramps – SEO, SEM, event marketing, direct community outreach etc. (btw SEO is totally under-rated as an on ramp). But don’t forget to explore paid and free channels on top of existing platforms & communities like eBay, Myspace, Facebook, Flickr, Instagram, Foursqaure etc etc.

Focus on The Registration Funnel First – The biggest variable that impact how fast a site/app can grow (mathematically) is actually not K but so called “viral cycle time” or “referral time” – it basically measures how long it takes to get an existing user to refer another user. For example, it is pretty much useless for an user to refer 2 more users after 1 year – even if EVERY user does it. As a result, the quickest way to achieve RAPID growth is to build registration into the core part of your viral loop – where you are shortening cycle time to as close to zero as possible. It also stakes a lot of creativity to make it work since some of the oldest tricks (remember the old “scan” your inbox for friends trick?) don’t work anymore. (Ro suggests taking a look @ schoolfeed.com for some inspiration). There are other benefits to focusing on the registration process first. For one, (not that it’s a sustainable situation) what if your site/app actually sucks? If it does, you wont be able to get people into the viral loop in the first place. The other benefit is that by focusing on the registration funnel and decreasing referral time, you will lessen your dependence on finding a scaled “on ramp” (see the last point).

Understand the Interactions Between Retention, Decay vs. Virality – Many of web 2.0’s first generation viral startups (rockyou, slide, hi5, tagged etc) never quite achieve the lofty promise they once held (not that those entrepreneur have anything to be ashamed of, they are still gods compared to us mortals) because of there are other equations besides customer acquisition that portend success. Customer retention (read satisfaction & engagement) is still king in the long run. You simply can’t have a leaky sieve and a rapidly decaying customer base even if you discovered the most viral acquisition channel known to the history of man. Pinterest is a great example of optimizing for acquisition AND retention – a moderately high K factor combined with a highly engaging product will also create a very large userbase AND eventually generate exponential growth once the userbase gets big enough.

Don’t Forget About Email – Not much to say except that email is one of the oldest customer acquisition and retention channels out there but decades later still underutilized. Don’t get too scared of your own shadows – let open and CTR rates determine the optimal frequency and call to action – push the envelope.

Explore New Channels – Don’t want to give away the farm here – but lots of industry insiders are raving about Facebook’s new Open Graph / Ticker integration and mobile app notifications (ipad in particular). Go dig in yourself.

Patrick Vlaskovits (Go Falcons!) was over at MuckerLab the other day talking to our companies about customer development which reminded me of the most important (only?) skill I took away in business school – segmentation. While “strategy” is the most over used word in business, “segmentation” is probably the most underutilized. It’s certainly not as sexy as “strategy” but it is the foundation from which any business is built. In a world of limited resources – a laser like focus on a few worthy target customers will help create efficiencies and purpose across the entire company from marketing, advertising, product management, engineering, – and yes, strategy.

The below are just some thoughts from Patrick’s presentation and my own experiences.

Choosing Segmentation Attributes

Its very easy to start the segmentation exercise thinking in terms of demographic information (my target customer is an Asian American male, 24-35, earning $50K a year etc ). Segmenting using these attributes is at best, lazy; and at worst, useless.

Does the difference in these attributes (male vs. female) explain the varying needs or pain points of each of the segments? E.g. I want widget X cause its cheaper vs. I want widget X cause it makes me look cool? If not, don’t use them.

Can my customers self identify through these attributes? Self discoverable attributes allows you (the startup) to qualify a customer/user through a simple questionnaire at the beginning of the engagement/funnel before investing too much resources in attempting to acquire that customer (or user).

Are the attributes unique to the market you are targeting? If your market is the offset printing industry – talking about demographic information of the owner might not be an useful exercise.

The Anti-Segment

It is really hard to get started in any segmentation exercise – often the best way to build some momentum is to understand who are NOT your customers. In most cases, at the end of the exercise you should have significantly more “anti-segments” than “target segments” – otherwise you haven’t really made the hard choice of selecting your customers and truly understanding who your best users/customers might be.

Make sure your segmentation scheme (Anti Segments + Target Segments) is “Mutually Exclusive and Collectively Exhaustive.” Its really bad to “miss” a segment because 1) that might be the segment you should be targeting 2) if you or someone at your company come across an user in that segment but put them in the wrong bucket (cause nothing fits) it will actually give you false readings for your hypothesis driven market tests.

Iteration & Segmentation

I like teams that are able to iterate at a high velocity. However; all too often, I see companies endlessly pivoting from market to market without really understanding WHY their initial product didn’t achieve market fit in the first place. One of the area to dig into as part of the iteration exercise is to “re-do” your segmentation scheme. If the user feedback on why they did not adopt the product is inconsistent WITHIN a segment, its highly likely you’ve screwed up the segmentation in the first place. As a result, instead of revamping product drastically, or pivoting to a whole new market – try re-segmenting the target customer base, rebuild your value hypothesis for a new segment, and make it another go.

Acquisition Channel & Segmentation – The “Usefulness” Test

Often, the created segmentation scheme looks good on paper but ends up pretty useless in practice. When there are no efficient, obvious, and cheap acquisition channels to reach a particular segment – its better to start over than to over compensate with impractical or expensive acquisition campaigns. Large companies have the marketing budget to only reach 25% or less of their intended segment with a mass market campaigns – startups don’t have that luxury and need to hit at least 75% efficiency on its acquisition spend. In terms of velocity and iteration testing – it will be next to impossible to get the right sample size, speed, and feedback loop if the acquisition channels do not match nicely with your segmentation scheme. This is why I typically stay away from using psychographic profiles as part of a segmentation model – there is just no simple or efficient marketing channels to reach, as an example, “upwardly mobile jet setting urban gen X’ers.”

Before Eric Ries, and even before Clay Christensen, there was Geoffrey Moore. Moore’s Crossing the Chasm was a seminal book at the time it was published in 1991, and should still be one of the very first book any entrepreneur reads. Back in those days, before the “internet” became an ubiquitous medium, the majority of the venture investments was in B2B – enterprise software, semiconductor, networking equipment, servers etc. Microsoft dominated the consumer software market (it had just wiped the floor with Lotus & Wordperfect) and Symantec took whatever crumb Microsoft deemed not sexy enough to go after (utilities!). Consumer hardware outside of PC’s was considered a low margin, short product lifecycle business better left to the Japanese.

Crossing the Chasm was written in a world where product were sold and not given away; a world where the sales person represented the last mile between a company and a customer. In that world, Geoffrey Moore’s book became the definitive guide to achieving the highly sought after hockey stick for entrepreneurs trying to introduce a disruptive innovation into a market. Geoff posits that there was a chasm between early adopters and the early majority and almost all startups fail not because they failed to find early adopters, but because they failed to make the jump through the chasm to the early majority. And to cross this chasm, entrepreneurs needed to dominate the first niche through offering a highly tailored product for that segment of users. Next, the entrepreneur needs to methodically capture additional adjacent niches through a “bowling pin” strategy until it is able to achieve some sort of scale and momentum. Once across the chasm, the goal is to redefine the competitive space and anoint oneself as the winner. The marketing focus is on “branding the space” and marketing to potential customers the necessity of buying a product in the category – not the company itself. (this was how the CRM war was created & won by Seibel). A must read synopsis here.

Of course, this was all before the Internet turned “mail order” and “publishing” into “e-commerce” and “web portal.” It was before Hotmail discovered virality, before eBay realized Metcalfe’s law, before Google re-invented intent, and before Facebook institutionalize word of mouth. eBay scaled almost effortlessly for over 5 years. Amazon tackled vertical to vertical until it was A to Z. Google search was a run away train that is still going. Youtube achieved escape velocity in 18 month. Facebook was a phenomenon that redefined the adoption curve for not just itself but companies on its platform. Twitter was part of the cultural zeitgeist almost since the day it was launched. To many people, Geoffrey Moore was just a worrywart who could not have predicted that the game itself would have changed.

For a time, it did seem like the rules that Moore had outlined didn’t apply as much anymore given how the internet upended much of the traditional technology business models and go to market strategies. (freemium, advertising, affiliate programs . . . sem, seo, viral, social). However lately, lots has been written on the struggles of some of the highest profile venture funded companies and the potential pile of living dead startups just barely holding on to their seed funding in the recent months. Whether they are just anecdotal stories or a trend that will realize itself into connectable data points is still been debated. What is true is that given the extreme valuation of well known startups on one end, the undeniable fact that VC’s are asking for significant business momentum at series A, and the shrinking venture capital pool in general – learning to efficiently cross the chasm will become increasingly important for any entrepreneur.

In the early parts of 2011, based on the valuation of startups getting funded, it did appear that many venture capitalists wrongly presumed that the “chasm” either no longer existed or that the companies they had invested in would have not problem crossing it.

A few of these companies are doing just fine, some haven’t really started executing their chasm strategies, and others have definitely hit the wall. For all of them, it is not a foregone conclusion that they would be able to “cross the chasm” and fulfill their promises as the next Google or eBay or Facebook. In fact, it would appear that the pendulum has swung in the other direction – that several market driven factors has made crossing the chasm harder than ever.

We are at the tail end of the first stage of the innovation cycle across multiple platforms (mobile, social, local) where hyper-competition, readily available capital, and the lower costs of starting a new venture have over saturated even niche opportunities where previously there would not have been a startup in that space in the first place. This has created a marketplace where every niche appear to have an incumbent (airbnb for XXX) making it extremely hard for even presumed market leaders (airbnb) to take on additional bowling pins. (Not mentioning the long term prospect of the derivative companies)

Many of today’s internet behemoths got here because they either relied on PR or leveraged at-the-time novel and cheap acquisition channels to grow their user bases. Hyper competition has made PR harder than ever. Direct acquisition channels that once helped scaled a large number of startups has either become too expensive (SEM), too competitive (SEO), or lost its effectiveness due to abuse (to some extend, social and email). Entrepreneurs now must be clever and relentless to find other acquisition channels to grow their company. (Celebrities? Craigslist?) – but the window for those channels are unpredictable, short, and most likely magnitude smaller than more scaled platforms.

Furthermore, the Internet has become so integrated into our daily lives and its reach so become pervasive that it is finally possible to build niche BRANDS on the internet (Warby Parker, J Hilburn, etc) without tens of millions of dollars spent on advertising. While branding creates long term equity and barrier to entry, it also limits potential adjacent market expansion opportunities. Brands are like quick drying concrete – they settle in consumer’s mind quickly and it is hard to change. The days where you can take a brand like eBay and apply it across multiple verticals or categories has pretty much ended.

Many of the current generation of startups have relied on social platforms to achieve their exponential user acquisition growth. The dark side of relying on those platforms for growth is that the users are more likely than not to belong to the same segment if not the same community. As a result, as the company starts moving across other communities and segments for additional growth, the incumbent community will either turn off new members or even worse – reject the new members completely.